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Investigation of proportional link linkage clustering methods
Authors:William H E Day  Herbert Edelsbrunner
Institution:(1) Department of Computer Science, Memorial University of Newfoundland, A1C 5S7 St. John's, Newfoundland, Canada;(2) Institute für Informationsverarbeitung, Technische Universität Graz, Schiesstattgasse 4a, A-8010 Graz, Austria
Abstract:Proportional link linkage (PLL) clustering methods are a parametric family of monotone invariant agglomerative hierarchical clustering methods. This family includes the single, minimedian, and complete linkage clustering methods as special cases; its members are used in psychological and ecological applications. Since the literature on clustering space distortion is oriented to quantitative input data, we adapt its basic concepts to input data with only ordinal significance and analyze the space distortion properties of PLL methods. To enable PLL methods to be used when the numbern of objects being clustered is large, we describe an efficient PLL algorithm that operates inO(n 2 logn) time andO(n 2) space.This work was partially supported by the Natural Sciences and Engineering Research Council of Canada and by the Austrian Fonds zur Förderung der wissenschaftlichen Forschung.
Keywords:Algorithm complexity  Algorithm design  Integer link linkage clustering method  Monotone invariance  SAHN clustering method  Space distortion
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